This research develops an assessment methodology to estimate traveler information benefits using regional travel demand and microscopic simulation approaches in combination. This method uses the strengths of the two conventional approaches in an innovative way, providing essentially a pseudo-dynamic model capability that uses readily available data and is easy to understand and implement. The pseudo-dynamic model provides measures of delay that are more reasonable than those available through either of the model sub-components individually;While attempts have been made to develop dynamic regional planning models, regional model "simulation" is not yet available. Therefore, the approach addresses several gaps in capabilities left by the use of simulation or regional models alone. For example, existing simulation models can not alter individual destination choices because origin-destination flows are assumed fixed. Further, as current methods assume that travelers have immediate and complete knowledge of the transportation system operation for making route choice decisions, a mix of knowledge levels is difficult to assess. The proposed approach also allows for a mix of optimal and sub-optimal (but perceived optimal) user choices, promulgated by various levels of traveler information which can be modeled to assess benefits of various strategies. The principal contribution of this research is the development of a pseudo-dynamic modeling environment suitable for assessing traveler information or other ITS services. The identification and combination of optimal and "perceived-optimal" paths in a regional network simulation is original to this work. The system allows region-wide assessment of pre-trip and en-route traveler information services and incorporates travel time feedback into the trip making and route selection processes. Specifically, the work provides a practical approach to assessing ITS improvements. In general, the work shows that conventional transportation modeling environments can be integrated to perform analyses of new transportation systems.